Shirley S. Pang

An ice-motion tracking system at the Alaska SAR facility

An operational system for extracting ice-motion information from synthetic aperture radar (SAR) imagery is being developed as part of the Alaska SAR Facility. This geophysical processing system (GPS) will derive ice-motion information by automated analysis of image sequences acquired by radars on the European ERS-1, Japanese ERS-1, and Canadian RADARSAT remote sensing satellites. The algorithm consists of a novel combination of feature-based and area-based techniques for the tracking of ice floes that undergo translation and rotation between imaging passes. The system performs automatic selection of the image pairs for input to the matching routines using an ice-motion estimator. It is designed to have a daily throughput of ten image pairs. A description is given of the GPS system, including an overview of the ice-motion-tracking algorithm, the system architecture, and the ice-motion products that will be available for distribution to geophysical data users. >

psi -s correlation and dynamic time warping: two methods for tracking ice floes in SAR images

The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the psi -s curve. The first algorithm uses normalized correlation to match the psi -s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented. >

A post-processing system for automated rectification and registration of spaceborne SAR imagery

Abstract An automated post-processing system has been developed that interfaces with the raw image output of the operational digital SAR correlator. This system is designed for optimal efficiency by using advanced signal processing hardware and an algorithm design that requires no operator interaction, such as the determination of ground control points. The standard output is a geocoded image product (i.e. resampled to a specified map projection). The system is capable of producing multiframe mosaics for large-scale mapping by combining images in both the along-track direction and adjacent cross-track swaths from ascending and descending passes over the same target area. The output products have absolute location uncertainty of less than 50 m and relative distortion (scale factor and skew) of less than 0.1 per cent relative to local variations from the assumed geoid.

Automated Multisensor Registration: Requirements And Techniques

A necessary first step in the fusion of data from a number of different remote sensors is the correction of the systematic geometric distortion characteristic of each sensor followed by a precision registration to remove any residual random offsets. This paper describes our approach to automated multisensor registration. The effects of spatially, temporally and spectrally varying factors which influence image dynamics are reviewed. A specification of the requirements for an operational algorithm is formulated using these factors. Additionally, the structure of an efficient, automated system is defined. A number of candidate image processing techniques are evaluated within this structure using a multisensor test data set assembled from the Landsat TM, SEASAT and SPOT sensors. The results are presented and discussed.

An automated system for mosaicking spaceborne SAR imagery

Abstract An automated system has been developed for mosaicking spaceborne synthetic aperture radar (SAR) imagery. The system is capable of producing multiframe mosaics for large-scale mapping by combining images in both the along-track direction and adjacent cross-track swaths from ascending and descending passes. The system requires no operator interaction and is capable of achieving high registration accuracy. The output product is a geocoded mosaic on a standard map grid such as UTM or polar stereographic. The procedure described in detail in this paper consists essentially of remapping the individual image frames into these standard grids, frame-to-frame image registration and radiometric smoothing of the seams. These procedures are directly applicable to both the Magellan Venus Mapper and a scanning SAR design such as Radarsat, Eos SAR in addition to merging image frames from traditional SAR systems such as SEASAT and SIR-B. With minor modifications, it may also be applied to spaceborne optical senso...

Improved Geometric Calibration of the Sir-C Data

Errors in the determination of the platform state vector (position and velocity) limits the accuracy with which individual pixels in a SAR image can be located. This paper will describe a method to up-date the state vector based on the SAR data itself. The algorithm combines reference targets at known locations with the estimates available from the mission control center, utilizing a Maximum Likelihood Estimator (MLE). The targets can be located at calibration sites or be easily recognizable targets of opportunity. The paper will discuss how the accuracy of the up-date depends on the number of targets, their geometry, and the accuracy of their position determination.The algorithm has been tested using SEASAT SAR data. High accuracy state vectors (0 = 10-20 m) were perturbed by Gaussian distributed errors with standard deviations and crosscorrelations based on worst case expectations for SIR-C. Tests using ground targets located in topographic maps (1:24000) showed that state vector position errors in the order of 300-400 m and velocity accuracies of 2-3 m/sec are readily achievable. Simulations have also shown that with accurately surveyed point target arrays, extending 50 to 100 km across and along track, accuracies on the order of 50 m in the location and 0.5 m/sec in the velocity are feasible.